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Updated: May 27, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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用XGBoost对单核酸多态数据进行高血压风险预测的特征选择.

Lailil Muflikhah1, Tirana Noor Fatyanosa1, Nashi Widodo2

  • 1Department of Informatics Engineering, Faculty of Computer Science, Brawijaya University, Malang, Indonesia.

Healthcare informatics research
|February 20, 2025
PubMed
概括

这项研究开发了一个XGBoost模型来识别292个单核酸多态 (SNP) 作为高血压生物标志物. 该模型实现了98%的准确性,为预测高血压风险提供了一个强大的新工具.

关键词:
遗传学 是一个遗传学.在高血压的高血压.机器 机器 机器 机器机器学习 机器学习预测方法 预测方法一个单核酸多态性多态性.

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